Implementing Importance Sampling in the Least-Squares Monte Carlo Approach for American Options
作者： Manuel Morales
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摘要: We illustrate how importance sampling can be implemented in the Least-Squares Monte-Carlo approach (LSM) introduced by Longsta and Schwartz (2001). The fact that LSM estimates optimal stopping rule, gives way to application of a change measure accelerate simulation. An Accelerated (ALSM) estimator is presented compared with straight forward LSM. rate convergence this empirically studied as function chosen measure. algorithm optimize choice discussed.
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